which is sub-optimal due to two reasons. First, a ranking model only ranks models within the same search space and does not allow comparing performance of different search spaces. Second, the simple sum of quality metrics does not take the potentially different noise-sensitivity of blocks into account, for which a weighted sensitivity model is required. The DONNA predictor takes on both roles.
Figure REF (right) illustrates the performance of the linear predictor for the DONNA search space and compares the quality of its ranking to DNA [1]}. Note that the quality of the DONNA predictor increases over time, as whenever Pareto-optimal networks are finetuned, they can be added to the Architecture Library, and the predictor can be fitted again.
